Salmon Tales: An Arts-Informed and Literary Inquiry into Salmon Farming in B.C.
Bibliographic record
Abstract
Dorothee Schreiber (2002) wrote two excellent articles that examine the framing of farmed fish and ways both commercial and food fishers from Ahousaht and Namgis First Nations make sense of salmon farms in their traditional territory.In detailing some of the risks in salmon farming, my goal is to continue to raise questions about any benefits from such a destructive industry.Salmon aquaculture or salmon farming is the industrial mass production of salmon.Farmed salmon are raised in floating net-cage pens located directly in the ocean and usually in coastal inlets.Each farm usually has 14 pens with each pen holding 50,000 fish providing each fish with a space of eight cubic feet (CAAR, 2002).In total, the 14 pens are the size of "three football fields" (CAAR, 2002, 5).In BC there are over approximately 140 salmon farm tenures with most of the product exported to the US, Japan, Taiwan, Korea (Living Oceans website).Currently, salmon farming occurs in places such as Chile, Scotland, Norway, US and both Pacific and Atlantic Canada. Environmental PollutionOn the surface, the practice of salmon farming would seem to be beneficial in terms of economic development, environmental preservation and food security.However, there are a number of documented risks associated with the practice. DiseaseDisease and parasite transfers such as sea lice can pose a threat to wild stocks.It is, because fish are in such close proximity, they are prone to disease and parasites.This has been particularly prevalent in the Broughton Archipelago, a place that holds the greatest concentration of fish farms in B.C. and has seen continuous declines in wild pink salmon returns in the past two years.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.014 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".